Principal Architect – Search, Recommendations & AI PlatformAbout Netcore UnbxdNetcore Unbxd is an AI-powered product discovery platform recognized by Forrester and Gartner as the global leader in Commerce Search and Product Discovery, earning Leader status in Gartner's 2025 Magic Quadrant™ for the second consecutive year. We're trusted by billion-dollar retailers like Unilever, Waitrose, Express, Puma, Signet, and Advance Auto Parts to power conversions and revenue through best-in-class product discovery and personalization. We're at the forefront of Agentic AI in commerce — building AI Shopping Assistants and Autonomous Merchandising Agents that redefine how shoppers find what they want.Curious what it's like to work here? Check out Life at Netcore - https://netcorecloud.Com/careers/Also Please have a look at our Founder's take on where we're headed: https://www.Founderthesis.Com/p/rajesh-jain-and-netcore-cloud-theRole OverviewWe're looking for a Principal Architect to own the technical direction of Unbxd's Search, Recommendations, and AI Engineering Platform — the core system processing millions of API calls a day across a multi-tenant SaaS platform, under tight SLAs, for some of the world's largest retailers. This is a senior individual-contributor role, not a people-management position. You'll be the deepest technical authority in the room: setting architecture strategy, making hard distributed-systems tradeoffs, and being hands-on enough to prototype, debug, and review code at the level of detail that actually moves the needle.You'll also act as a technical advisor across adjacent areas of the platform — including the Merchandising Console and other supporting systems — helping ensure architectural coherence across Unbxd's broader product surface, even though your primary charter is search, recommendations, and the AI engineering platform.Experience:



12+ years in software engineering, with 8+ years of demonstrable architecture-level ownership of large-scale, high-throughput distributed systems.Core Skills: Java, Go, Python; deep expertise in information retrieval systems (Solr/Lucene or equivalent); distributed systems fundamentals (consensus, sharding, replication, caching, queuing); production experience with vector search / embedding-based retrieval and its integration into traditional search stacks.Key ResponsibilitiesOwn and evolve the architecture of Unbxd's Search & Recommendations platform — a Solr-based system supporting millions of API calls/day at strict SLA targets for enterprise retail customers.Set the multi-year technical strategy for the AI Engineering Platform, including how vector search, embeddings, and LLM-based agentic components (AI Shopping Assistant, Autonomous Merchandising Agents) integrate with the core retrieval stack.Make and defend architectural decisions on scalability, fault tolerance, multi-tenancy, and cost-efficiency for a SaaS platform operating at retail scale (including peak-traffic events like flash sales and holiday spikes).Act as a technical advisor to adjacent teams (Merchandising Console, self-serve, delivery/CX platforms), ensuring their designs align with overall platform architecture, without owning their day-to-day delivery.Stay hands-on — write and review code, build proofs of concept for new architectural directions,



and go deep on production issues when systemic root-causing is needed.Partner with engineering leadership, product management, and customer-facing teams to translate business and customer requirements (e.G., SLA commitments, billing model design, integration patterns for SIs/agencies) into sound technical architecture.Define technical standards, review architecture proposals across teams, and act as an escalation point for the hardest distributed-systems and reliability problems.Represent Unbxd's technical platform in customer-facing or partner-facing technical discussions where deep architectural credibility is required.Track and evaluate emerging technology (search, vector databases, agentic AI infra) and translate it into pragmatic recommendations for the platform roadmap.Qualifications8+ years architecting and operating large-scale distributed systems in production, ideally in search, recommendations, or a related high-QPS domain.Strong, current coding ability — this is an IC role and hands-on technical depth is non-negotiable, not a legacy credential.Proven experience with information retrieval systems (Solr, Elasticsearch, Lucene, or similar) at scale.Practical experience integrating vector search / embedding-based retrieval with traditional keyword search systems.Track record of operating systems under strict SLA/availability commitments in a multi-tenant SaaS workplace.Experience influencing architecture across multiple teams/domains without formal reporting authority — strong technical persuasion and cross-functional collaboration skills.Comfortable making build-vs-buy and cost-vs-performance tradeoffs at a platform level (e.G., billing model design, infra migration strategy).Prior exposure to agentic AI systems or LLM-based production features is a strong plus, given Unbxd's direction into Agentic AI.

📌 Principal Architect (Bengaluru)
🏢 Netcore Unbxd
📍 Bengaluru